In vehicle tire pressure monitoring systems, the TPMS must determine the exact sensor location (e.g. front left (FL), front right (FR), rear left (RL), or rear right (RR)) in order to correctly identify the location of the tire with low pressure. The location can then be displayed by the system (for example, in a dashboard TPMS display unit). A determination of the location of a particular tire is often referred to as “tire localization.” A determination of the location of a particular tire made automatically by the TPMS itself is often referred to as “automatic tire localization.”
Generally, solutions for automatic tire localization use correlations between the phase information of TPS and anti-lock brake system (ABS) WSS signals. There are two typical approaches to these solutions.
According to a first approach, a TPS sends radio frequency (RF) signal(s) only when the TPS reaches a single predetermined reference position. A TPMS receiver, for example, an electronic control unit (ECU), receives the RF signal and calculates the tire location based on the angular position and WSS counter information that was acquired at the moment the RF signal was received.
There are several disadvantages in this first approach. The most common way to detect the phase (angle) of a TPS is to use an acceleration senor in the TPS module for motion detection. Most TPS therefore have at least one acceleration sensor or shock sensor. A measuring of the TPS phase and frequency requires some time to be collected (a “sampling time”). In another disadvantage of this first approach, the TPS also requires some additional time to calculate the phase and frequency information for a given sampling data set due to limitation of CPU processing time (a “processing time”). In yet another disadvantage of this first approach, an RF transmission at the single fixed phase) must wait until the TPS reaches the reference position (a “waiting time”) to transmit the RF frame. This waiting time can be calculated by an extrapolation method based on the phase and frequency information of given sample points. Sampling time delays and processing time delays are typical across many tire localization solutions. However, waiting time is an additional delay unique to the aforementioned first approach.
Furthermore, waiting time depends on the vehicle speed and the time sampling and processing time was conducted. Effectively, the waiting time is a random value, and can range between a few microseconds second up to a few hundred milliseconds, because the moment at which data is sampled is random (phase and time are random) but also the vehicle speed (and wheel radius) is effectively random. This waiting time directly effects energy consumption and battery life, which is one of most critical design factors of TPMS applications. During the waiting time, the CPU of the TPS has to consume more energy because most CPUs cannot enter a low energy mode because the TPS must keep a high resolution and accurate time tracking. Additionally, the waiting time can increase the phase error if the waiting time is long and the vehicle undergoes acceleration or deceleration during the extrapolation period. Further, most OEM TPMSs specify a guideline for the RF transmission interval. If the vehicle speed is low, the TPS can potentially be out of specification with the OEM regulation.
According to a second approach, a TPS sends an RF frame, wherein the RF frame includes angular position and time information for when the angular position was measured. A TPMS receiver, for example, an ECU, receives the RF signal and calculates each tire location based on the angular position, time information, and WSS counter information that was acquired for the moment the angular position was measured.
There are several disadvantages in this second approach. The RF frame must include additional time and phase information that frames of other approaches, such as the frame of the first approach described above. A longer frame length can have more current consumption compared to shorter RF frame lengths at the same conditions. In another disadvantage of this second approach, the failure rate for RF transmission/receiving can be increased due to the longer data frame. In yet another disadvantage of this second approach, the ECU receiver must record WSS counter values for each wheel and store the WSS counter values for some duration, which requires additional memory space compared to other approaches. Likewise, the ECU receiver must incorporate complex processing instructions in order to search the WSS counter values for each wheel.